DBMS > HBase vs. Impala vs. Redis

System Properties Comparison HBase vs. Impala vs. Redis

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Analytic DBMS for Hadoop

In-memory data structure store, used as database, cache and message broker info

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Wide column store

Relational DBMS

Key-value store info

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Document store

Document store info

with Redis Modules
Graph DBMS info

with Redis Modules
Search engine info

with Redis Modules
Time Series DBMS info

with Redis Modules

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	49.11
Rank	#22	Overall
	#2	Wide column stores

Score	15.52
Rank	#36	Overall
	#22	Relational DBMS

Score	152.87
Rank	#7	Overall
	#1	Key-value stores

Website

hbase.apache.org

www.cloudera.com/products/open-source/apache-hadoop/impala.html

redis.io

Technical documentation

hbase.apache.org

www.cloudera.com/documentation/enterprise/latest/topics/impala.html

redis.io/documentation

Developer

Apache Software Foundation info

Apache top-level project, originally developed by Powerset

Cloudera

Salvatore Sanfilippo info

Development sponsored by Redis Labs

Initial release

2008

2013

2009

Current release

2.2.0, June 2019

3.3.0, August 2019

6.0.6, July 2020

License

Commercial or Open Source

Open Source info

Apache version 2

Open Source info

Apache Version 2

Open Source info

BSD 3-Clause, commercial license available

Cloud-based only info

Only available as a cloud service

DBaaS offerings (sponsored links) info

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows info

using Cygwin

Linux

BSD
Linux
OS X
Windows info

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

XML support info

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

proprietary protocol info

RESP - REdis Serialization Protocol

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts info

Stored procedures

yes

Coprocessors in Java

yes

user defined functions and integration of map-reduce

Lua

Triggers

yes

Partitioning methods info

Methods for storing different data on different nodes

Sharding

Replication methods info

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication info

with Redis Enterprise Pack
Source-replica replication info

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts info

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys info

Referential integrity

Transaction concepts info

Support to ensure data integrity after non-atomic manipulations of data

Single row ACID (across millions of columns)

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency info

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability info

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities info

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts info

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users, groups and roles info

based on Apache Sentry and Kerberos

Simple password-based access control info

Access control lists and SSL are available in the commercial version

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